ENGINEERING DESIGN OPTIMIZATION USING A SWARM WITH AN INTELLIGENT INFORMATION SHARING AMONG INDIVIDUALS
ENGINEERING DESIGN OPTIMIZATION USING A SWARM WITH AN INTELLIGENT INFORMATION SHARING AMONG INDIVIDUALS
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DOI：
10.1080/03052150108940941
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发表时间：
2001-08
影响因子：
2.7
通讯作者：
T. Ray;Pankaj Saini
中科院分区：
文献类型：
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作者：
T. Ray;Pankaj Saini
本文提出了一种新的求解单目标设计优化问题的群体算法。群体是具有共同目标以达到函数的最佳值(最小值或最大值)的个体的集合。在群体中的个体中，有一些表现更好的个体(领导者)，他们为其余的个体设定了寻找的方向。不在较好表现者名单(BPL)中的个人通过从BPL中最近的邻居那里获取信息来提高其表现。在无约束问题中，使用目标值来生成BPL，而对于约束问题，则采用多层Pareto排序来生成BPL。信息共享策略还确保群中的所有个体都是唯一的，就像在真实的群中一样，在给定的时刻，两个个体不能共享相同的位置。个体之间的独特性导致在最后阶段产生一组近乎最优的个体，这对灵敏度分析是有用的。用三个经过充分研究的工程设计实例说明了所提出的群体策略的好处。
Abstract In this paper a new swarm algorithm for single objective design optimization problems is presented. A swarm is a collection of individuals having a common goal to reach the best value (minimum or maximum) of a function. Among the individuals in a swarm, there are some better performers (leaders) who set the direction of search for the rest of the individuals. An individual that is not in the better performer list (BPL) improves its performance by deriving information from its closest neighbour in the BPL. In an unconstrained problem, the objective values are used to generate the BPL while a multilevel Pareto ranking scheme is implemented to generate the BPL for constrained problems. The information sharing strategy also ensures that all the individuals in the swarm are unique as in a real swarm, where at a given time instant two individuals cannot share the same location. The uniqueness among the individuals result in a set of near optimal individuals at the final stage that is useful for sensitivity analysis. Three well-studied engineering design examples are solved to illustrate the benefits of the proposed swarm strategy